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Level of IL-6 predicts respiratory failure in hospitalized symptomatic COVID-19 patients (preprint)
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.04.01.20047381
ABSTRACT
The pandemic Coronavirus-disease 19 (COVID-19) is characterized by a heterogeneous clinical course. While most patients experience only mild symptoms, a relevant proportion develop severe disease progression with increasing hypoxia up to acute respiratory distress syndrome. The substantial number of patients with severe disease have strained intensive care capacities to an unprecedented level. Owing to the highly variable course and lack of reliable predictors for deterioration, we aimed to identify variables that allow the prediction of patients with a high risk of respiratory failure and need of mechanical ventilation Patients with PCR proven symptomatic COVID-19 infection hospitalized at our institution from 29th February to 27th March 2020 (n=40) were analyzed for baseline clinical and laboratory findings. Patients requiring mechanical ventilation 13/40 (32.5%) did not differ in age, comorbidities, radiological findings, respiratory rate or qSofa score. However, elevated interleukin-6 (IL-6) was strongly associated with the need for mechanical ventilation (p=1.2.10-5). In addition, the maximal IL-6 level (cutoff 80 pg/ml) for each patient during disease predicted respiratory failure with high accuracy (p=1.7.10-8, AUC=0.98). The risk of respiratory failure for patients with IL-6 levels of [≥] 80 pg/ml was 22 times higher compared to patients with lower IL-6 levels. In the current situation with overwhelmed intensive care units and overcrowded emergency rooms, correct triage of patients in need of intensive care is crucial. Our study shows that IL-6 is an effective marker that might be able to predict upcoming respiratory failure with high accuracy and help physicians correctly allocate patients at an early stage.

Full text: Available Collection: Preprints Database: medRxiv Language: English Year: 2020 Document Type: Preprint

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Full text: Available Collection: Preprints Database: medRxiv Language: English Year: 2020 Document Type: Preprint